Computational analyses are playing an increasingly central role in research. Journals, funders, and other researchers are calling for published research to include associated data and code. However, many researchers have not received training in best practices and tools for sharing code and data.
This is a step-by-step, practical workshop to prepare your research code and data for computationally reproducible publication. The workshop starts with some brief introductory information about computational reproducibility, but the bulk of the workshop is guided work with code and data. We cover the basic best practices for publishing code and data. Participants move through best practices for organizing their files, preparing their code for reuse, documentation, and submitting their code and data to share using Code Ocean.
Prerequisites: Participants should bring their own data, code, and laptop.
Audience: Researchers who use code in their research and wish to share it.
Learn best practices for file organization, documentation, automation, and dissemination.
Assess possible tools for publishing code and data.
Submit your code and data for publishing on Code Ocean.
Xu Fei's role as an outreach scientist at Code Ocean includes helping researchers make their work more reproducible and sharing computational reproducibility best practices with the research community. He has a Master's degree in neuroscience.